With the recent development of the Internet of Things (IoT), simulation or virtual modeling has rapidly grown in the fields of energy (e.g., oil platforms, wind turbines, power plants, solar panels, etc.), healthcare (e.g., diagnostic equipment, treatment equipment, etc.), transportation (e.g., aircraft, locomotives, automobiles, etc.) as well as many others. A digital twin, or a virtual model, refers to a computerized model that corresponds to a real physical asset such as a product, process, or service. The digital twin is often generated based on data received from the physical asset. Here, the data can be obtained from sensors installed on the physical asset which may be used to model a status, working condition, and position of the physical asset in virtual space. This pairing of the virtual and physical worlds allows analysis of data and monitoring of physical assets to address problems before they even occur, prevent downtime, develop new opportunities, and plan for the future based on simulations.
The digital twin is often meant to be an up-to-date and accurate digital replica of the properties and states of the corresponding physical asset, which may include one or more of shape, position, gesture, status, and motion. However, related art virtual modeling approaches are limited in number, type and location of physical sensor installations within a physical structure. Another issue with acquiring data from physical sensors such as accelerometers, gauges, motion sensors, and the like, attached to the asset is that the physical sensors cost money to acquire, install, and maintain. Furthermore, sensor data can be vast and difficult to sift through in real-time. Currently, sensor analysis does not provide sufficient real-time analysis of sensor readings and results in a poor assessment of the state of a physical structure at a given time. In addition, preprogrammed and simplified (generic) mathematical algorithms used for digital conversion and structure analysis become inadequate upon changed needs or conditions, for example, when the physical structure begins to deteriorate or complex scenarios develop in and around the physical asset. Accordingly, what is needed is an improved way of monitoring and diagnosing a physical asset through a virtual asset in real-time.
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